/hand-gesture-to-voice-converter-and-wheel-chair-controller

hand-gesture-to-voice-converter-and-wheel-chair-controller

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hand-gesture-to-voice-converter-and-wheel-chair-controller

For video reference : https://www.linkedin.com/posts/anubrata-shil-348a75208_smarthandgloves-accessibility-innovation-activity-7175560815620603904-UvgW?utm_source=share&utm_medium=member_desktop

🔹 Gesture to Voice Converter: The default mode empowers users with seamless gesture recognition, seamlessly translating hand movements into clear and concise voice commands. This feature is a game-changer for individuals with speech impairments or those seeking hands-free communication, significantly enhancing accessibility.

🔹 Wheelchair Control: The second mode shatters barriers by offering intuitive wheelchair control functionalities. By harnessing natural hand gestures, users gain precise and effortless control over their wheelchairs, fostering newfound independence and mobility.

Purpose-driven at its core, the project is committed to:

🎯 Enhancing Accessibility: By bridging the gap between gesture recognition technology and real-world applications, we're driving towards a more inclusive society.

🌐 **Fostering Independence:**It will empower individuals with disabilities to navigate their environments and communicate effectively, championing independence and autonomy.

🚀 Driving Innovation: The relentless pursuit of pushing boundaries in assistive technology is paving the way for future advancements and opportunities.

Technologies Utilized:

  1. Microcontrollers: Esp32 (for smart gloves), Arduino Uno (for wheelchair).
  2. Flex sensor (for gesture sensing).
  3. Df mini player (MP3 playback).
  4. NRF transceiver.
  5. Motor driver L298N.

Software Utilized: Arduino IDE.

Communication Protocols Utilized: UART, SPI.

Stay tuned for forthcoming blogs detailing the project's components and operational functionality. I invite you to share any insights you find intriguing and valuable.